WATER-GS: Watermark-embedded 3D Gaussian Splatting via Plug-and-play Decoder

Yuqi Tan, Xiang Liu, Shuzhao Xie, Bin Chen, Shu-Tao Xia, Zhi Wang

Keywords: 3D gaussian splatting, digital watermarking

TL;DR: A novel method designed to protect 3DGS copyrights through a plug-and-play strategy.

Abstract: 3D Gaussian Splatting (3DGS) has emerged as a pivotal technique for 3D scene representation, providing rapid rendering speeds and high fidelity. As 3DGS gains prominence, safeguarding its intellectual property becomes increasingly crucial since 3DGS could be used to imitate unauthorized scene creations and raise copyright issues. Existing watermarking methods for implicit NeRFs cannot be directly applied to 3DGS due to its explicit representation and real-time rendering process, leaving watermarking for 3DGS largely unexplored. In response, we propose WATER-GS, a novel method designed to protect 3DGS copyrights through a plug-and-play strategy. First, we introduce a pre-trained watermark decoder, treating raw 3DGS generative modules as potential watermark encoders to ensure imperceptibility. Additionally, we implement novel 3D distortion layers to enhance the robustness of the embedded watermark against common real-world distortions of point cloud data. Comprehensive experiments and ablation studies demonstrate that WATER-GS effectively embeds imperceptible and robust watermarks into 3DGS without compromising rendering efficiency and quality. Our experiments indicate that the 3D distortion layers can yield up to a 20% improvement in accuracy rate. Notably, our method is adaptable to different 3DGS variants, including 3DGS compression frameworks and 2D Gaussian splatting.

Primary Area: alignment, fairness, safety, privacy, and societal considerations

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Submission Number: 4123